AIMC Topic: Child, Preschool

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Artificial intelligence as an analytic approximation to evaluate associations between parental feeding behaviours and excess weight in Colombian preschoolers.

The British journal of nutrition
Parental practices can affect children's weight and BMI and may even be related to a high prevalence of obesity. Therefore, the aim of this study was to evaluate the relationship between parents' practices related to feeding their children and excess...

Bone age assessment based on deep convolution neural network incorporated with segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Bone age assessment is not only an important means of assessing maturity of adolescents, but also plays an indispensable role in the fields of orthodontics, kinematics, pediatrics, forensic science, etc. Most studies, however, do not take in...

The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication and stereotyped behavior. Unlike typicall...

Preschoolers' Motivation to Over-Imitate Humans and Robots.

Child development
From preschool age, humans tend to imitate causally irrelevant actions-they over-imitate. This study investigated whether children over-imitate even when they know a more efficient task solution and whether they imitate irrelevant actions equally fro...

Application of Machine Learning Techniques for Enuresis Prediction in Children.

European journal of pediatric surgery : official journal of Austrian Association of Pediatric Surgery ... [et al] = Zeitschrift fur Kinderchirurgie
INTRODUCTION:  As a subset of artificial intelligence, machine learning techniques (MLTs) may evaluate very large and raw datasets. In this study, the aim is to establish a model by MLT for the prediction of enuresis in children.

Robot-assisted laparoscopic unroofing and fulguration of sequestered caliceal diverticula cluster.

Journal of pediatric urology
INTRODUCTION: We report a rare case of four sequestered caliceal diverticula that failed previous percutaneous sclerotherapy and were subsequently managed with robot-assisted laparoscopic unroofing and fulguration of the sequestered diverticula clust...

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor d...